small tweaks

app.py

@@ -22,8 +22,8 @@ def respond_passage_finder(message):
     output = []
     for doc in documents:
         quotes = doc.metadata.get('matched_quotes', [])
-        publication = doc.metadata.get('publication_name', 'Unknown Publication')
-        chapter = doc.metadata.get('chapter_name', 'Unknown Chapter')
+        publication = doc.metadata.get('book_name', 'Unknown Publication')
+        chapter = doc.metadata.get('full_title', 'Unknown Chapter')
         full_passage = doc.metadata.get('highlighted_content', '')
         
         quote_text = "\n".join([f"• \"{q.quote}\"" for q in quotes])
@@ -62,7 +62,7 @@ def respond_chatbot(query, history):
     passages = ''
     if documents and len(documents) > 0:
         for d in documents:
-            passages += f'<b>{d.metadata["publication_name"]} - {d.metadata["chapter_name"]}</b>\n{d.page_content}\n\n'
+            passages += f'<b>{d.metadata["book_name"]} - {d.metadata["full_title"]}</b>\n{d.page_content}\n\n'
         history.append((f'Passages: {query}', passages))
     response = result["messages"][-1].content
     system_message_dropdown = state.get("system_message_dropdown")
@@ -80,7 +80,7 @@ def respond_genericchatbot(query, history):
     passages = ''
     if documents and len(documents) > 0:
         for d in documents:
-            passages += f'<b>{d.metadata["publication_name"]} - {d.metadata["chapter_name"]}</b>\n{d.page_content}\n\n'
+            passages += f'<b>{d.metadata["book_name"]} - {d.metadata["full_title"]}</b>\n{d.page_content}\n\n'
         history.append((f'Passages: {query}', passages))
     response = result["messages"][-1].content
     history.append((query, response))
@@ -136,9 +136,9 @@ with gr.Blocks(css=css) as demo:
             
             output_area_pf = gr.HTML()
             
-            gr.Markdown("### Sources")
-            gr.Textbox(value="Journey to Self Realization, Second Coming of Christ, and Autobiography of a Yogi", 
-                       label="Available Sources", interactive=False)
+            # gr.Markdown("### Sources")
+            # gr.Textbox(value="Journey to Self Realization, Second Coming of Christ, and Autobiography of a Yogi", 
+            #            label="Available Sources", interactive=False)
             
             submit_btn_pf.click(process_input_passage_finder, inputs=input_text_pf, outputs=output_area_pf)
 
@@ -156,7 +156,7 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 with gr.Column(scale=4):
                     chatbot_output = gr.Chatbot(height=600)
-                    user_input_cb = gr.Textbox(placeholder="Type your question here...", label="Your Question", value="What is the meaning of life?")
+                    user_input_cb = gr.Textbox(placeholder="Type your question here...", label="Your Question")
                     submit_button_cb = gr.Button("Submit")
                 
                 with gr.Column(scale=1):
@@ -180,16 +180,16 @@ with gr.Blocks(css=css) as demo:
                     )
 
                     
-                    gr.Markdown("""
-                    <div class="source-box">
-                        <strong>Available sources:</strong>
-                        <ul>
-                            <li>Journey to Self-Realization</li>
-                            <li>The Second Coming of Christ</li>
-                            <li>Autobiography of a Yogi</li>
-                        </ul>
-                    </div>
-                    """)
+                    # gr.Markdown("""
+                    # <div class="source-box">
+                    #     <strong>Available sources:</strong>
+                    #     <ul>
+                    #         <li>Journey to Self-Realization</li>
+                    #         <li>The Second Coming of Christ</li>
+                    #         <li>Autobiography of a Yogi</li>
+                    #     </ul>
+                    # </div>
+                    # """)
             
             # system_prompt_dropdown.change(
             #     fn=lambda x: (sp.chatbot_descriptions[x], sp.system_prompt_templates[x]),
@@ -228,7 +228,7 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 with gr.Column(scale=4):
                     generic_chatbot_output = gr.Chatbot(height=600)
-                    user_input_gc = gr.Textbox(placeholder="Type your question here...", label="Your Question", value="Loaves and fishes")
+                    user_input_gc = gr.Textbox(placeholder="Type your instructions and question here...", label="Your Instructions and Question")
                     submit_button_gc = gr.Button("Submit")
 
             # ... (existing code for the column with markdown)
@@ -245,9 +245,9 @@ with gr.Blocks(css=css) as demo:
 
             gr.Examples(
                 examples=[
-                    "Tell me about Paramahansa Yogananda's life",
-                    "What are the main teachings of Self-Realization Fellowship?",
-                    "Explain the concept of Kriya Yoga",
+                    "Help me brainstorm ideas for a spiritual talk on the topic of cultivating divine love?",
+                    "How would I explain this to a beginneron the path: What are the main teachings of Self-Realization Fellowship?",
+                    "Explain the concept of Kriya Yoga for an advanced kriya yogi",
                     "Can you provide quotes about the importance of meditation?",
                 ],
                 inputs=user_input_gc,

src/generic_bot.py

@@ -37,7 +37,7 @@ class ToolManager:
 
     def add_tools(self):
         @tool
-        def vector_search(query: str, k: int = 5) -> list[Document]:
+        def vector_search(query: str, k: int = 15) -> list[Document]:
             """Useful for simple queries. This tool will search a vector database for passages from the teachings of Paramhansa Yogananda and other publications from the Self Realization Fellowship (SRF).
             The user has the option to specify the number of passages they want the search to return, otherwise the number of passages will be set to the default value."""
             retriever = self.vectorstore.as_retriever(search_kwargs={"k": k})
@@ -45,7 +45,7 @@ class ToolManager:
             return documents
              
         @tool
-        def multiple_query_vector_search(query: str, k: int = 5) -> list[Document]:
+        def multiple_query_vector_search(query: str, k: int = 15) -> list[Document]:
             """Useful when the user's query is vague, complex, or involves multiple concepts. 
             This tool will write multiple versions of the user's query and search the vector database for relevant passages. 
             Use this tool when the user asks for an in depth answer to their question."""

src/passage_finder.py

@@ -51,7 +51,7 @@ class ToolManager:
 
     def add_tools(self):
         @tool
-        def vector_search(query: str, k: int = 10) -> list[Document]:
+        def vector_search(query: str, k: int = 15) -> list[Document]:
             """Useful for simple queries. This tool will search a vector database for passages from the teachings of Paramhansa Yogananda and other publications from the Self Realization Fellowship (SRF).
             The user has the option to specify the number of passages they want the search to return, otherwise the number of passages will be set to the default value."""
             retriever = self.vectorstore.as_retriever(search_kwargs={"k": k})
@@ -171,7 +171,7 @@ class QuoteFinder:
         docs = state["documents"]
         final_response = ""
         for doc in docs:
-            final_response += doc.metadata["publication_name"] + ": " + doc.metadata["chapter_name"] + "\n" + doc.metadata["highlighted_content"] + "\n\n"
+            final_response += doc.metadata["book_name"] + ": " + doc.metadata["full_title"] + "\n" + doc.metadata["highlighted_content"] + "\n\n"
 
         return {"final_response": final_response}
 

src/srf_bot.py

@@ -37,7 +37,7 @@ class ToolManager:
 
     def add_tools(self):
         @tool
-        def vector_search(query: str, k: int = 5) -> list[Document]:
+        def vector_search(query: str, k: int = 15) -> list[Document]:
             """Useful for simple queries. This tool will search a vector database for passages from the teachings of Paramhansa Yogananda and other publications from the Self Realization Fellowship (SRF).
             The user has the option to specify the number of passages they want the search to return, otherwise the number of passages will be set to the default value."""
             retriever = self.vectorstore.as_retriever(search_kwargs={"k": k})
@@ -45,7 +45,7 @@ class ToolManager:
             return documents
              
         @tool
-        def multiple_query_vector_search(query: str, k: int = 5) -> list[Document]:
+        def multiple_query_vector_search(query: str, k: int = 15) -> list[Document]:
             """Useful when the user's query is vague, complex, or involves multiple concepts. 
             This tool will write multiple versions of the user's query and search the vector database for relevant passages. 
             Use this tool when the user asks for an in depth answer to their question."""